The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
Open accessAbstract
Maximum likelihood parameter estimation and sampling from Bayesian posterior distributions are problematic when the probability density for the parameter of interest involves an intractable normalising constant which is also a function of that parameter. In this paper, an auxiliary variable method is presented which requires only that independent samples can be drawn from the unnormalised density at any particular parameter value. The proposal distribution is constructed so that the normalising constant cancels from the Metropolis-Hastings ratio. The method is illustrated by producing posterior samples for parameters of the Ising model given a particular lattice realisation.
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Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Weak convergence and optimal scaling of random walk Metropolis algorithms
Roberts, G. O., Gelman, A., & Gilks, W. R. (1997) · The Annals of Applied Probability · doi:10.1214/aoap/1034625254 · Cited by 1,693
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Modern Statistics for Spatial Point Processes*
MØLLER, J., & WAAGEPETERSEN, R. P. (2007) · Scandinavian Journal of Statistics · doi:10.1111/j.1467-9469.2007.00569.x · Cited by 305
Self-citationMarkov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy
Sharma, S. (2017) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev-astro-082214-122339 · Cited by 298
MCMC for doubly-intractable distributions
Murray, I., Ghahramani, Z., & Mackay, D. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1206.6848 · Cited by 281
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Grelaud, A., Marin, J.-M., Robert, C. P., Rodolphe, F., & Taly, J.-F. (2009) · Bayesian Analysis · doi:10.1214/09-ba412 · Cited by 119
Metadata
- Authors
- Møller, J., Pettitt, A. N., Reeves, R., & Berthelsen, K. K.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-06-01
- Volume
- 93
- Issue
- 2
- Pages
- 451-458
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2125280835
- Cited by
- 352
- References
- 2
- FWCI
- 9.76
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Møller, J., Pettitt, A. N., Reeves, R., & Berthelsen, K. K. (2006). An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants. Biometrika. https://doi.org/10.1093/biomet/93.2.451
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